Morphological Signal Processing for Phenotype Recognition of Human Pluripotent Stem Cells Using Machine Learning Methods
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data
2.2. Classification Models
2.3. Feature Selection
2.4. Statistical Methods
3. Results
3.1. Classification Models for Cellular and Colonial Data
3.2. Classification Models for Combined Cellular and Colonial Data
3.3. Importance of Morphological Parameters in Classification Models
4. Discussion
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Method | Cellular Data | Colonial Data | ||
---|---|---|---|---|
Accuracy | ROC AUC | Accuracy | ROC AUC | |
Naïve Bayes | 58 ± 2% | 0.69 | 60 ± 14% | 0.71 |
k-nearest neighbors | 64 ± 3% | 0.66 | 68 ± 12% | 0.71 |
Logistic regression | 59 ± 4% | 0.63 | 75 ± 12% | 0.90 |
Random forest | 64 ± 2% | 0.67 | 66 ± 10% | 0.79 |
Support vector machines | 64 ± 3% | 0.68 | 68 ± 11% | 0.86 |
Artificial neural networks | 67 ± 4% | 0.70 | 71 ± 12% | 0.89 |
Accuracy | |||
---|---|---|---|
hESC H9 | hiPSC AD3 | hiPSC CaSR | |
Cellular data (artificial neural networks) | 73 ± 7% | 60 ± 6% | 64 ± 3% |
Colonial data (logistic regression) | 75 ± 18% | 62 ± 20% | 67 ± 17% |
Method | Accuracy | ROC AUC |
---|---|---|
Naïve Bayes | 72 ± 7% | 0.815 |
k-nearest neighbors | 88 ± 4% | 0.818 |
Logistic regression | 80 ± 6% | 0.826 |
Random forest | 99 ± 2% | 0.997 |
Support vector machines | 96 ± 2% | 0.975 |
Artificial neural networks | 98 ± 2% | 0.956 |
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Vedeneeva, E.; Gursky, V.; Samsonova, M.; Neganova, I. Morphological Signal Processing for Phenotype Recognition of Human Pluripotent Stem Cells Using Machine Learning Methods. Biomedicines 2023, 11, 3005. https://0-doi-org.brum.beds.ac.uk/10.3390/biomedicines11113005
Vedeneeva E, Gursky V, Samsonova M, Neganova I. Morphological Signal Processing for Phenotype Recognition of Human Pluripotent Stem Cells Using Machine Learning Methods. Biomedicines. 2023; 11(11):3005. https://0-doi-org.brum.beds.ac.uk/10.3390/biomedicines11113005
Chicago/Turabian StyleVedeneeva, Ekaterina, Vitaly Gursky, Maria Samsonova, and Irina Neganova. 2023. "Morphological Signal Processing for Phenotype Recognition of Human Pluripotent Stem Cells Using Machine Learning Methods" Biomedicines 11, no. 11: 3005. https://0-doi-org.brum.beds.ac.uk/10.3390/biomedicines11113005